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  • 标题:Hybrid an Improvement Water Flow-like Algorithm with Single Based Metaheuristic for CVRP
  • 本地全文:下载
  • 作者:Zulaiha Ali Othman ; Mokhtar Massoud Kerwad ; Suhaila Zainudin
  • 期刊名称:International Journal of Computer Science and Network Security
  • 印刷版ISSN:1738-7906
  • 出版年度:2019
  • 卷号:19
  • 期号:9
  • 页码:40-48
  • 出版社:International Journal of Computer Science and Network Security
  • 摘要:Water-flow-like algorithm (WFA) has shown a reasonable solution for the Capacitated Vehicle Routing Problem (CVRP). However, applying the basic WFA has problems in terms of slow convergence and being faster trapped in the local optimum and later it has been improved it quality solution at precipitation mechanism especially on diversification strategic at precipitation operation known as IWFA. However, the diversification strategy only solved exploration problem rather than exploitation. Therefore, this paper aims to propose a hybrid IWFA with single-solution-based metaheuristics to overcome the problem. Four algorithms which are Best Improvement (BI), First Improvement (FI), Great Deluge (GD) and Simulated Annealing (SA) have been tested. Experiments were conducted using the Standard CVRP dataset benchmark. The experiment results show that Hybrid IWFA with Great Deluge has obtained the best solution. The proposed algorithm not only be able to obtain the benchmark solution for small datasets similar state of art algorithm but it's also able to obtain better solution for large datasets compare with the state of art algorithm faster.
  • 关键词:Water- flow like algorithm; CVRP; Great Deluge; Hybrid metaheuristic
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